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针对传统TOPSIS法的不足,提出一种膨胀土分类的改进TOPSIS法。选取能充分反映膨胀土胀缩特性的液限、塑性指数、小于2μm胶粒含量与自由膨胀率为指标进行分析。综合考虑样本数据的波动信息与独立信息,采用独立信息数据波动(DIDF)赋权法确定权重。然后将灰色关联分析(GRA)与TOPSIS法融合,结合指标权重计算指标分类标准与待分类样本的贴近度。通过比较样本与各类别贴近度的大小确定所属类别,同时还可对同一类别膨胀土胀缩性进行排序,为工程建设提供更详细的参考依据。最后,选取2个工程实例共3 2个膨胀土样本对所建立模型进行验证。结果表明,该方法分类结果与实际较吻合,准确率平均达9 0.6 3%,能满足工程需要。
Aimed at the deficiency of traditional TOPSIS method, an improved TOPSIS method for expansive soil classification was proposed. The liquid limit, plasticity index, the content of micelles less than 2 μm and the free expansion rate can be selected as indexes to fully reflect the swelling and shrinking characteristics of expansive soil. Considering the volatility information and independent information of the sample data synthetically, the weight is determined by the independent information data fluctuation (DIDF) weighting method. Then the gray relational analysis (GRA) is combined with the TOPSIS method, and the closeness between the index classification standard and the sample to be classified is calculated by combining the index weight. By comparing the sample with the size of each category close to determine the type, and also the same category of expansive expansive soil to sort, provide a more detailed reference for the construction. Finally, a total of 32 samples of expansive soil from two engineering projects were selected to verify the model. The results show that the classification results of the method are in good agreement with the actual, the average accuracy rate of 9 0.6 3%, to meet the needs of the project.